tuesdata <- tidytuesdayR::tt_load('2021-08-31')
tuesdata <- tidytuesdayR::tt_load(2021, week = 36)
bird_baths <- tuesdata$bird_baths
library(shiny)
library(plotly)

survey_year <- unique(bird_baths$survey_year)
urural <- unique(bird_baths$urban_rural)
bioregions <- unique(bird_baths$bioregions)

print(survey_year)
[1] 2014 2015   NA
print(urural)
[1] "Urban" "Rural" NA     
print(bioregions)
 [1] "South Eastern Queensland" "NSW North Coast"          "Sydney Basin"             "South Eastern Highlands" 
 [5] "South East Coastal Plain" "Brigalow Belt South"      "NSW South Western Slopes" "Victorian Volcanic Plain"
 [9] "Victorian Midlands"       "Flinders Lofty Block"     NA                        
urbanrural <- df %>%
  group_by(survey_year, urban_rural) %>%
  count(sort = TRUE)
y <- c('giraffes', 'orangutans', 'monkeys')
SF_Zoo <- c(20, 14, 23)
LA_Zoo <- c(12, 18, 29)
data <- data.frame(y, SF_Zoo, LA_Zoo)

fig <- plot_ly(data, x = ~SF_Zoo, y = ~y, type = 'bar', orientation = 'h', name = 'SF Zoo',
        marker = list(color = 'rgba(246, 78, 139, 0.6)',
                      line = list(color = 'rgba(246, 78, 139, 1.0)',
                                  width = 3)))
fig <- fig %>% add_trace(x = ~LA_Zoo, name = 'LA Zoo',
            marker = list(color = 'rgba(58, 71, 80, 0.6)',
                          line = list(color = 'rgba(58, 71, 80, 1.0)',
                                      width = 3)))
fig <- fig %>% layout(barmode = 'stack',
         xaxis = list(title = ""),
         yaxis = list(title =""))

fig
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